In recent years, deep learning has been widely used in the field of image un- derstanding and made breakthroughs research progress in image under- standing. Because remote sensingapplication and image understanding are inseparable, researchers have carried out a lot of research on the application of deep learning in remote sensing field, and extended the deep learning me- thod to various application fields of remote sensing. This paper summarizes the basic principles of deep learning and its research progress and typical ap- plications in remote sensing, introduces the current main deep learning mod- el and its development history, focuses on the analysis and elaboration of the research status of deep learning in remote sensing image classification, object detection and change detection, and on this basis, summarizes the typical ap- plications and their application effects. Finally, according to the current ap- plication of deep learning in remote sensing, the main problems and future development directions are summarized.
In this paper design proposed architecture for the remote sensingapplication. The three main units comprises the advanced framework the three units are First, Remote sensing data accession unit (RSDU) takes the information from the satellite and transfers to the earth Station, wherever processing starts in this unit. Second, Data processing unit (DPU) is the main role in the architecture, the real time data will process efficiently by filtering, load balancing and parallel processing and Third, Data Analyzing and Decision unit (DADU) this unit is responsible for the storing the output and generates the opinion based on the results of the data processing unit.
Foliage is often much more intensive in IR images and some semitransparent objects may become transparent in IR wavelengths and vice versa. One possible solution comes from the field of data fusion of these images with different contents could be utilized to enhance image quality of object if suitable cameras are available. A number of methods have been proposed for merging infrared images with visible spectrum images concentrate heavily on the surveillance and remote sensing applications . Fusion methods can be broadly classified into two that is spatial and transform domain fusion. But spatial domain methods such as Averaging, Brovery, and Principle Component Analysis (PCA) based methods produce spectral distortion in the fused image. This is particularly crucial in remote sensing if images to merge were not taken at the same time. In the last few years, multi-resolution analysis has become one of the most promising methods for the analysis of images in remote sensing. Recently proposed new approach to image merging that uses a multi- resolution analysis procedure based upon wavelet transform. The DWT and SWT based method will be more efficient for fusion. Stationary Wavelet Transform (SWT) is similar to Discrete Wavelet Transform (DWT) but the only process of down-sampling is suppressed that means the SWT is translation-invariant . But the image fusion algorithm based on DWT is faster developed image fusion method in recent decade. Discrete Wavelet Transform has good time frequency characteristics. DWT is defined as considering the wavelet transform of the two registered input images (Infrared and Visible) together with the fusion rule. Then, the inverse wavelet transform is computed, and the fused image is reconstructed.
In the project described herein, it’s the first time to develop an electrochemical sensor based on a GCE electrode modified with ISO and GO (ISO/GO/GCE), which is not only sensitive to Hg 2+ , but also broaden the application of ISO in electrochemistry. During the electrochemical detection process, the redox reaction happened between the free methoxy and phenolic hydroxyl groups of the ISO, as shown in scheme 1 .
Remote sensors from the Satellite or Aircrafts are generated by huge volume of data which can utilize for impending signification if collected data aggregated effectively incorporates by insight information. Data is collection from simple to hybrid devices, which are continuously working for technology around us and communicate with each other. These devices are transferring huge amounts of real time data daily. The transaction added to the synchronized inaccessible sensing data that is retrieving the useful information in the proficient way of classification in the direction of the severe computational challenges, analyze, the assortment, and accumulate, where gathered data is inaccessible. The real time sensing devices will continuously export data. In this work, we will implement the big data analytics on remote sensing datasets. We utilized BEST software for header analysis of the datasets and retrieving the full resolution image from the dataset. Then retrieved image is divided into smaller blocks for applying statistical. By applying certain rules and conditions in the form of algorithm, determine the land and sea blocks of image dataset. Our end results are proficiently analyzing real-time remote sensing utilizing the land beacon structure. Finally, a comprehensive investigation of the remotely intelligence earth beacon massive information for earth and ocean space are available by utilizing- Hadoop.
Accelerometer is an electronic device used to measure the activity of vibration and shock which present in all areas of our daily lives. They may be generated and transmitted by motors, turbines, machine-tools etc. In this project, a low cost accelerometer device is developed for the use of measuring vibration level from vibration sources such as motor engine, machineries with a simple set-up using piezoelectric cantilever. The accelerometer is developed using easily available piezoelectric materials with physical area about a few cm 2 (3cm x 5cm) which can easily mounted in the form of a cantilever. The piezoelectric cantilever was obtained off-the-shelf and tailor made to suit to the application as an accelerometer. The accelerometer was designed to operate at frequency higher than its resonant frequency so that a linear response would be produced. At this said frequency, the voltage output is proportional to the magnitude of the acceleration level (g-level), therefore the level of the vibration from any sources with excitation frequency higher than the piezoelectric cantilever structure natural frequency can be measured. However, at frequency range outside from resonant, the voltage output produced by the piezoelectric accelerometer is small and very difficult to measure accurately due to measurement noise. Therefore, amplifier circuit was developed to amplifier the small signal from the accelerometer before being measured and analyzed.
In the past decade, graphene and layered material such as Transition metal dichalcogenides (TMDs) and Transition metal oxides (TMOs) have been investigated for their importance in several applications. For example, these materials can be used in several fields such as energy storage and sensing device production; additionally, some of these important devices need to be scaled up for mass production. In this work, production of 2D material has been performed by liquid phase exfoliation (LPE) and the nanosheet study has been followed by strain sensor fabrication, incorporating the nanosheet in a polymeric matrix. Afterwards, a statistical computer program has been used to build a scheme able to predict the interactions between the composite variables. These predictions describe when and how the results are dependent on different variables.
DOI: 10.4236/gep.2017.58018 228 Journal of Geoscience and Environment Protection product classification, the vegetation area of Shanghai is divided into green land (forest), grassland and cultivated land of three classes (Figure 4 from Shanghai city and satellite remote sensingapplication center). As can be seen from the map areas which has more green land such as Nanhui, Pudong, Songjiang, Fengxian have larger average change of vegetation water supply index. There is something to do with the green land (Woodland) has developed roots which can fully absorb the deep soil moisture so that it has a certain resistance to water and heat environment. And the reason why the amount of green land (Woodland) increased most is because of the root system of the role of infiltration, which in- creased soil pore in order to save more rain.
The Visible and Infrared Multispectral Imager (VIMI) is one of the main payloads of the GF-5 satellite. It has 12 spectral bands covering the wave- length from visible light to thermal infrared. The imager designed life is 8 years. In order to monitor and correct the radiometric performance of the imager for a long time and meet the user’s demand for the quantitative re- mote sensingapplication, the expandable diffuser used for calibration in full FOV and full optical path method is designed. The solar diffuser is installed on the front side of the optical system and does not affect the normal imaging of VIMI. When VIMI need calibration, the diffuser is expand to the front of optical system via the driving mechanism. According to the characteristics of the GF-5 satellite orbit, the requirement of the calibration energy and the in- stallation matrix of the imager relative to the satellite, the expansion angle of the diffuser is 39 degrees. The 430 mm × 430 mm large-size PTEE diffuser is manufactured to ensure full FOV and full optical path calibration. The dif- fuser’s directional hemispherical reflectance is higher than 95% from 420 nm to 2400 nm and variation of BRDF in the direction of imager observation is better than 2.5%. The diffuser stability monitoring radiometer is designed to monitor the on-orbit attenuation performance of the diffuser. Results of ground simulation experiments and preliminary on-board calibration expe- riments were introduced.
In rugged mountains as a result of terrain the effective illumination of pixels varies considerably. In a remote sensing image the pixel on shady slope receives weak illumination and has a low radiance value, in contrast the pixel on the sunny slope receives strong illumination and has a high radiance value. For the same object the pixel radiance value on the shady will be different from that on the sunny slope. Additionally, different objects may have similar radiance values. These ambiguities seriously affected remote sensing image information extraction accuracy in mountainous areas. It became the main obstacle to further application of remote sensing image the purpose of topographic correction is to eliminate this effect, recovering the true reflectivity or radiance of objects in horizontal conditions. It the premise of quantitative remote sensingapplication.
Realizing the importance of Remote sensing technology in Disaster management the State Remote SensingApplication Centre, Itanagar (SRSAC), completed Hazard Zonation of Arunachal Pradesh pertaining to landslides, floods and earthquake on 1:50K scale (DMIS, 2008). The term "landslide" refers to the downward and outward movement of slope-forming materials like rocks, soil, sediments, artificial fills or a combination of these (Varnes, 1978). The Landslide Hazard Zonation (LHZ) maps on 1:50K scale is the first attempt by SRSAC to find out the vulnerable zones in Arunachal Pradesh as per the guidelines suggested for landslide hazard zonation in mountainous terrain by the Bureau of Indian Standards (BIS 1998). Major factors that influence the occurrence of landslides are lithology, structure, slope, geomorphology, land use/land cover, forest density, relative relief, anthropogenic reasons and rainfall (Fig.2). Slope facet, which is defined as a part of hill slope having more or less similar characters of slope showing consistent slope direction and inclination is considered as the smallest unit for the study (DMIS, 2008). Cumulative weightages were calculated by adding ratings of individual sub-parameters for each facet. Based on the cumulative weightages the LHZ is classified into five hazard zones such as very high, high, moderate, low and very low (Fig.3). The methodology was validated by overlaying the landslide incidence map over the LHZ map (DMIS, 2008). The LHZ maps are important macro-scale (1:50K) information for all the developmental projects in the state for analyzing and designing the new projects against the possible landslide threat. For that reason the database was shared with all the State Government line departments and to the Govt. of India programme, ‘National Database for Emergency Management Mission (NDEM)’. In Figure 3, the high-resolution satellite image shows the active landslide at Karsingsa on National Highway 52A. This landslide falls in the very high hazard zone in the LHZ map. The Karsingsa landslide is active in nature owing to continuous toe cutting by the Dikrong river. The flow of land mass at Karsingsa is termed as static liquefaction by Sharmah and Singh (2011). Several research institutions are engaged in research for management and mitigation of Karsingsa landslide including early warning yet almost every year the community face crisis at Karsingsa.
KEYWORDS: Fiber optic sensor, Intrinsic Sensor, Application Based Sensors, Evanescent Wave, Evanescent wave for SensingApplication, Evanescent Absorption Coefficient, sensitivity of evanescent sensor, Simplest Evanescent Field Absorption Sensor, Experiment Set Up Details For Measuring The Nitrite Concentration In Water, Graph of absorption coefficient with concentration for different lengths, Power detected, sensitivity of sensor.
showed the best results as total resistance changed by 4 orders in 11%-95% RH range . Yongsheng et al. prepared ZnO nanorod and nanobelt films on the Si substrates with comb type Pt electrodes by the vapor-phase transport method. They found that at room temperature, resistance changed by more than four and two orders of magnitude when ZnO nanobelt and nanorod devices were exposed respectively to a moisture pulse of 97% relative humidity . Jayanti et al. doped ZnO nanocrystals with impurities of Li, Na, Cu, Pr, and Mg under similar conditions by solid-state reaction method. Their study showed that undoped ZnO, Li and Na doped ZnO showed well-developed nanorods but Cu doped ZnO nanorods were not well-formed, rather they tended to form clusters . Pandey et al. studied moisture sensingapplication of Cu 2 O
Speed sensingapplication can be achieved with a variety of approaches. One of the known famous solutions is to use a ferrous metal gear with a gear tooth sensor. Basically, the gear tooth sensor is the magnetic pick-up coil. The gear tooth will pass by the sensor face which will focuses and concentrates on the magnetic flux from the bias magnet in the sensor. The gear tooth sensor will detect the change in the flux level and translates it into a change in the sensor output.
ABSTRACT: Railway is best media for transportation, travelling. Nowadays, use of sensing technology is tremendously increased and widely used in various application field. In this paper, we have proposed system for automation in railway industry with the help of zigbee technology with wireless sensor network. In the railway industry, monitoring of different structural parts rail tracks, wheels, boogies, chassis, wagons from remote location in smarter way reducing human presence in actual rail field. In this paper we proposed automation in railway industry with the help of zigbee based WSN network. By placing WSN node on each structural part which wants to monitor. These sensor data is uploaded on webpage. Using mobile internet facility, data can be easily accessed from anywhere. Proposed system is best for detecting progressively worse situation in rail structural parts before condition turns to accident. Accidents happening due to track misalignment, over weighted boogies in train have been a big problem for railways for life security and timely management of services. This bending angle of tracks required to be identified in real time before a train actually comes near to the defected track and get subjected to an accident. In this paper, different types of rail fault analysis and monitoring methods are described and it used a basic algorithm is readdressed that makes use of wireless sensors for detecting faults in rail tracks beds, boogies and misalignment in the rail tracks. KEYWORDS: LPC2148 ARM7 Development Board, zigbee module, GSM SIM 800 modem, wireless sensor network
This paper focus on Sensing Enterprise and IoT applied in production systems. Thanks to the new information technologies, production processes can be optimized; the entire lifecycle of objects, from production to disposal can be monitored; and greater transparency can be gained about the status of the shop floor, the location and disposition of lots, and the status of production machines (Bandyopadhyay et Sen, 2011). Enterprises could take these advantages and improve their production system applying IoT.
Finally, the high Q-factor of waveguide cavities, often touted as one of the strengths of these de- vices, is potentially a weakness when attempting to integrate the cavity into a moisture sensing instrument. In order to locate the resonant frequency of the cavity with a test sample in place, the system oscillator must be capable of sweeping over a range of frequencies. However, the high Q-factor of the cavity means that the resonant ‘dip’ in the magnitude of the measured in- put reflection coefficient will be extremely narrow-band. In order to locate the minimum value of this dip with any accuracy, the oscillator must be able to sweep in very small frequency increments and its spectral purity must be high. As a result the digital control circuitry must be designed so that a wide range of demand frequencies can be ‘dialled up’ in sufficiently small steps, i.e. a high-resolution D/A converter will be required. These requirements all drive up the cost and complexity of an instrument based on a waveguide cavity sensor.